Contents

CKG2019 is concerned with knowledge graphs with contexts, i.e., every fact is enriched by the contexts (e.g., provenance, time, location, or confidence). Contextualized Knowledge Graphs (CKGs) have been gaining importance in the recent years. Research topics include contextualized and distributed Description Logics, annotation of statements in the Semantic Web, and Distributed Knowledge Repositories. Real-world use cases include the creation of collaborative knowledge bases, such as Wikidata, where qualifiers and references can be attached to every statement. This workshop aims to serve as a gathering point for researchers and industry interested in CKGs to discuss current challenges and future solutions, and raise awareness about this emerging topic to a more broader Semantic Web community. This workshop addresses fundamental as well as practical topics including (i) logical models to encode the contextual annotations in the graph, (ii) reasoning and querying over CKGs, (iii) using CKGs in applications such as query answering, data mining, or machine learning, (iv) techniques to benchmark or improve the performance of CKG storage and querying systems. This workshop is complemented by a W3C community on this topic.

The rise of knowledge graphs in the industry over the last decade with Google Knowledge Graph, Facebook’s Entity Graph, Microsoft’s Satori, Apple’s Siri, and Amazon’s True Knowledge has shown the maturity and the high impact of the Semantic technologies. At the same time, we have seen a raise in interest in adding contextual annotations to statements in Knowledge Graphs, with different research communities proposing solutions for representing, reasoning, and querying this knowledge, to actual initiatives to create Knowledge Graphs with contextual annotations, such as Yago, Wikidata, or The Open Knowledge Network.

The Open Knowledge Network (OKN), a community effort led by the Big Data Interagency Working Group (IWG) 10 at NITRD, has the vision to create an open knowledge graph of all public, private, and government sectors. OKN is meant to be an inclusive, open, and community-driven, resulting in a knowledge infrastructure that could facilitate and empower a host of applications and open new research avenues including how to create trustworthy knowledge networks in the form of CKGs. CKGs for answering more complex questions requires the contextual information to be incorporated to the data model. The complex questions are ranging from the macro (have there been unusual clusters of earthquakes in the US in the past six months?) to the micro (what is the best combination of chemotherapeutic drugs for a 56 y/o female with stage 3 glioblastoma and an FLT3 mutation but no symptoms of AML?). While three OKN workshops have been held largely focused on understanding the requirements and building a community, the proposed workshop will be a technical and technological counterpart for OKN workshops.

Paper submission and reviewing for this workshop will be electronic via EasyChair. The papers should be written in English, following the Springer LNCS format, and be submitted in PDF on or before June 28, 2019.

CKG2019 explicitly welcomes alternative and enhanced submission formats, such as communicative online materials. Authors who are preparing such a submission should contact the workshop organizers in advance to make sure we can accommodate for them in the submission and review process. All deadlines are midnight Hawaii time.

The following types of contributions are welcome.

Full research papers (8 pages)

Position papers (4-6 pages)

Short research papers (4-6 pages)

System/tool papers (4-6 pages)

We especially welcome the papers describing the datasets and use cases with contextual information such as provenance, time, location, certainty, and probability.